Method and machine controller for controlling a machine

A computer-implemented method for controlling a machine, comprising:

• a) reading in a plurality of first training data sets in each of which an operating state of the machine has an associated control action;
• b) generating further training data sets, using the operating states and control actions specified in the first training data sets, with new associations between operating states and control actions, so that a respective operating state is assigned multiple alternative control actions;
• c) training a machine learning module with the first training data sets and the further training data sets to take an operating state and a control action as a basis for predicting a machine performance accumulated over a state trajectory of consecutive operating states as a resulting output value, with:
• an operating state subsequent to a particular considered operating state in a state trajectory being determined by feeding, for each of the alternative control actions associated with the considered operating state, the considered operating state and the respective alternative control action into the machine learning module, taking the resulting output values of the machine learning module as a basis for selecting one of the alternative control actions, and using a simulator of the machine to determine an operating state that results from application of the selected control action to the considered operating state as the subsequent operating state,
• a performance evaluator being used to determine a performance value accumulated over the operating states of a respective state trajectory, and
• the machine learning module being trained to reproduce the determined accumulated performance values;
• and
• d) controlling the machine by:
• detecting a current operating state of the machine,
• predicting an accumulated performance for each of the alternative control actions associated with the current operating state by the trained machine learning module,
• actuating the machine using a control action that optimizes the predicted accumulated performance, and
• if the optimizing control action is not executed successfully, selecting another of the alternative control actions on the basis of the accumulated performance thereof to control the machine.